the Air Vent

Because the world needs another opinion

Gridded Comparison of Temperature Metrics

Posted by Jeff Id on October 21, 2009

Chad at TreesfortheForest has done a post I was hoping to do at some point.   He’s compared the different temperature metrics on a gridded basis.  I found the results surprising.  Check it out.


I had begun calculations for a post on urban warming, but as usual, I got sidetracked on something else. This is that sidetrack. There’s much interest in the differences in the RSS and UAH temperature data sets. We’ve seen plenty of graphs showing the difference in the spatial averages of both data sets. But I think we can learn more by looking at the differences between the gridded data. I took the difference between UAH and RSS from January 1979 – Sept 2009 and calculated the trend at each grid point.


As you can see, there is strong differential warming of RSS relative to UAH in the tropics. This probably explains why Santer’s analysis of tropical tropospheric amplification went well with RSS and not so much with UAH. Outside of the tropics, the differential warming is in the opposite direction but dependent on hemisphere with UAH in the lead in the North. Approaching the North Pole, the differential warming becomes unmistakably larger and larger. However, approaching the South Pole, the warming rises, then at about 50° S, it starts to drop. I remember reading that RSS’s correction of diurnal drift is latitude dependent, but I couldn’t find the paper or website where I found it. If anyone knows if this is true, I’d appreciate a reference. Here’s the zonal trend.


Read the rest here.

21 Responses to “Gridded Comparison of Temperature Metrics”

  1. timetochooseagain said

    From what I’ve seen, UAH as a group has done a number of papers showing that UAH has the best agreement with balloon datasets at all locations.

    Anyway, this is definitely interesting. I wonder what it looks like before and after the “jump” that several groups have identified in RSS in about 1992.

    And RSS’s diurnal correction makes use of a climate model. I’m not sure how that works, but that is what they do, and I would imagine that would change with latitude. Of course, I don’t think that is the issue, since my understanding is that over the oceans, diurnal correction is hardly needed. There seems to be a lot of differences over land and ocean.

  2. Layman Lurker said

    Wow, what a striking graphic. Chad, I think your hunch may be right about latitude dependant corrections.

    Here is a document published by Carl Mears Feb. 2007 describing the changes between RSS version 2.1 and version 3:

    Intersatellite offsets now vary as a function of latitude. This leads to changes in the long-term trends when plotted as a function of latitude. These changes are fairly small for TLT, TMT, and TLS, but quite large for TTS (MSU3/AMSU7). The intersatellite offsets for MSU3 are strong functions of latitude, with the later satellites (NOAA-14 and NOAA-12) showing substantially different offsets when compared to the earlier satellites (NOAA-10 and NOAA-11). This coherence between the later satellites results in a large change in the long-term trends as a function of latitude. This difference is large enough that earlier versions of TTS should be considered to be wrong.

  3. Chad said

    Jeff, thanks for the shoutout. I’ve update the post with a quick comparison of the pre- and post-1992 periods.

  4. Jeff Id said

    Wow, that’s interesting. I sent an email to Dr. Christy asking if he could take a look at your results and perhaps shed some light.

  5. Chad said

    Cool. Christy has always been prompt and very helpful with my inquiries to him.

  6. Jeff Id said

    Me too. A very nice guy to accept and answer questions from someone out of nowhere. His comments gave me an understanding of the latest science he was working on.

  7. Ryan O said

    Jeff, where did you get gridded UAH data? I suppose I could look myself, but I’m too lazy. Haha. 🙂

  8. Chad said

    The UAH gridded data is available at . The data are in files that end in a year (they’re about 616 K). The readme ( should assist you in reading it into R.

  9. Ryan O said

    Sweet. Thanks.

  10. Geoff Sherrington said

    Previously I have asked why the southern parts of continents seem to show cold blue belts around their seashores. Maybe I have been looking at the wrong datasets. It is of significance for studies of the Antarctic where most of the manned stations are on the coastline, though coverage varies with the satellite.

    Any ideas on why the blue is there? I don’t know, I’m hoping to be educated.

  11. Andrew said

    10-My understanding is that for MSU’s there is a concern that sea ice interferes with the measurement of brightness temperatures.

  12. Jeff Id said

    #10, I’m not sure yet.

  13. Layman Lurker said

    Andrew (TTCA), on Chad’s blog you observed: “RSS minus GISS has a weird El Nino signature. What’s up with that?”. I believe this might be evidence of tropospheric amplification in the ENSO signature region. This is particularly interesting when recalling Jeff’s series of posts comparing UAH, GISS, and RSS. I think it evolved into the tropospheric amplification issue in this post (followed by several others):

    The strange thing is that global tropospheric amplification was evident on short term time scales but reversed over time. And yet Chad’s graphics are over 30 years and the amplification pattern persists in the signature region.

  14. timetochooseagain said

    13-Maybe the data is really good? I shrug my shoulders, really.

    My suspicion is that amplification is correct, more or less, but the surface data exaggerates the warming. Which would explain why the trend isn’t amplified, but the variability is.

  15. Layman Lurker said

    Funny, I was pretty much thinking the same thing. 😉 If long term amplification trend is going to overcome biased surface station data anywhere, it will show up in the tropics (where amplification is strongest) vis a vis a signature pattern like ENSO. I wonder if GISS was “re-trended” by the UHI factor suspected by McKitrick whether the global tropospheric amplification trends might present themselves in the differences.

  16. timetochooseagain said

    15-Well, actually, it looks like the land surface data in the tropics is very bad quality, but then amplification is, according to Gavin, stronger over the ocean. That, and of course there are no urban heat islands over the ocean! 🙂

    But what’s really weird is that the ENSO region really shows up well in RSS minus GISS, but NOT as any other comparison of surface and sat. There is a weak ENSO area in UAH minus GISS, and there are hints of it around the same area in HadCrut and NOAA, but Chad’s pics show, oddly, little data in the ENSO region for those two…

    Well, anyway, all curious stuff.

  17. Layman Lurker said


    I think the ENSO pattern in RSS (compared to UAH) has been brought out by the 1992 step and the relative tropical bias of RSS vs. UAH. Everything in the tropics is just scaled up a tad.

  18. timetochooseagain said

    That would probably help.

  19. Layman Lurker said

    In this case the RSS minus UAH relative bias “adjusts” the RSS metric just enough that we get this curious ENSO amplification signature (like the visible tip of an iceberg) in RSS which runs contray to the puzzle of short time scale vs. long time scale amplification. This begs the question…Why? Is there a physical reason for this or is it just an (very revealing) artifact of the various biases in the metrics.

    Intuitively, I would lean toward the “artifact” explanation as just playing around with the linear trends behind UAH minus GISS would likely bring out the same signature. Of course, there are many who would argue what the true source of the trend biases are which obscure long term tropospheric amplification.

  20. dougie said


    “That, and of course there are no urban heat islands over the ocean!”

    check out

    may be relevant

  21. […] you can see, there is strong differential warming of RSS relative to UAH in the tropics. This probably explains why Santer’s analysis of tropical tropospheric amplification went well with RSS and not so much with UAH. … […]

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